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Journal of Intelligent Manufacturing

, Volume 30, Issue 3, pp 1099–1110 | Cite as

Nonstationary signal analysis and support vector machine based classification for vibration based characterization and monitoring of slit valves in semiconductor manufacturing

  • M. Musselman
  • H. Xie
  • D. DjurdjanovicEmail author
Article
  • 237 Downloads

Abstract

Slit valves play an important role in semiconductor manufacturing, enabling creation and maintaining of a vacuum environment required for wafer processing. Due to the high volume of production in the modern semiconductor industry, slit valves could experience severe degradation over their lifetime. If maintenance is not applied in due time, degraded valves may lead to defects in finished products due to pressure loss and particle generation. In this paper, we propose methods for signal processing and feature extraction for analysis of slit valve vibration signals. These methods are then used to demonstrate the ability to reliably, accurately and efficiently distinguish between vibration patterns of each individual valve via a multi-class classification procedure. Furthermore, instantaneous time–frequency entropy of valve vibrations enabled long term monitoring of a slit valve in production, in spite of variations in valve speed and operations.

Keywords

Slit valves Semiconductor manufacturing Vibrations based monitoring Nonstationary signal analysis Multi-class classification 

Notes

Acknowledgements

This research is supported in part by the National Science Foundation (NSF) grant IIP 1266279. The content of this paper is solely the responsibility of the authors and does not represent the official views of the NSF.

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Lam Research CorporationFremontUSA
  2. 2.Department of Mechanical EngineeringUniversity of TexasAustinUSA

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